18 citations · 31 across the 14 of their papers we have counts for
7 papers · 1 filter
ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models
Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu +8
LLMs can solve complex tasks by generating long, multi-step reasoning chains. Test-time scaling (TTS) can further improve performance by sampling multiple variants of intermediate…
Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
Anka Reuel, Avijit Ghosh, Jenny Chim +32
Foundation models are increasingly central to high-stakes AI systems, and governance frameworks now depend on evaluations to assess their risks and capabilities. Although general c…
Chimera: Diagnosing Shortcut Learning in Visual-Language Understanding
Ziheng Chi, Yifan Hou, Chenxi Pang +3
Diagrams convey symbolic information in a visual format rather than a linear stream of words, making them especially challenging for AI models to process. While recent evaluations…
Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning
Yucheng Wang, Yifan Hou, Aydin Javadov +2
Multimodal large language models (MLLMs) promise enhanced reasoning by integrating diverse inputs such as text, vision, and audio. Yet cross-modal reasoning remains underexplored,…
Real Time Captioning of Sign Language Gestures in Video Meetings
Sharanya Mukherjee, Md Hishaam Akhtar, Kannadasan R
It has always been a rather tough task to communicate with someone possessing a hearing impairment. One of the most tested ways to establish such a communication is through the use…
LEXam: Benchmarking Legal Reasoning on 340 Law Exams
Yu Fan, Jingwei Ni, Jakob Merane +14
Long-form legal reasoning remains a key challenge for large language models (LLMs) in spite of recent advances in test-time scaling. To address this, we introduce LEXam, a novel be…
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
Shaona Ghosh, Heather Frase, Adina Williams +99
The rapid advancement and deployment of AI systems have created an urgent need for standard safety-evaluation frameworks. This paper introduces AILuminate v1.0, the first comprehen…